DocumentCode :
3648094
Title :
Evolutionary design of local binary pattern feature shapes for object detection
Author :
Filip Kadlček;Otto Fucik
Author_Institution :
Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
137
Lastpage :
144
Abstract :
This paper deals with the evolutionary design of application specific feature shapes of Local Binary Pattern (LBP) features for object detection in image processing applications. LBP features are very often utilized in image classification systems which are used for pattern recognition. By using genetic algorithm the application of specific weak classifiers´ feature shapes, which are highly optimized to achieve a better accuracy of the AdaBoost strong classifier, are being evolved.
Keywords :
"Shape","Accuracy","Genetic algorithms","Training","Field programmable gate arrays","Biological cells","Feature extraction"
Publisher :
ieee
Conference_Titel :
Adaptive Hardware and Systems (AHS), 2012 NASA/ESA Conference on
Print_ISBN :
978-1-4673-1915-7
Type :
conf
DOI :
10.1109/AHS.2012.6268641
Filename :
6268641
Link To Document :
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